Compare Any service

Pricing Model

Time & Materials, Fixed Fee, Retainer

Commercial Flexibility

Gainshare Models, Fixed Fee Projects, Retainer-Based, FTE Augmentation, Outcome-Based Pricing

Gainshare / Outcome Pricing

Gainshare, Performance-Based Savings Share

Delivery Model

On-Site, Remote, Hybrid

Pricing Model

Time & Materials, Gainshare, Outcome-Based

Commercial Flexibility

Outcome-Based Pricing, Fixed-Price Engagements, Hybrid Models

Gainshare / Outcome Pricing

Percent of Savings Achieved, Fixed Outcome Targets

Delivery Model

Onsite, Remote, Hybrid

Typical Integration Time

6–12 weeks

Middleware Experience

ETL platforms, Data warehousing, Cloud data lakes

Certified Partnerships

SAP, Oracle, Coupa

Proprietary Accelerators

true

Typical Integration Time

4–8 weeks (discovery and data onboarding)

Middleware Experience

REST APIs, Webhooks, EDI, SFTP, Cloud connectors

Certified Partnerships

Coupa, SAP Ariba, Jaggr

Proprietary Accelerators

Spend Analytics Framework, Supplier Risk Dashboard, Category Playbooks, Benchmarking Engine

AI-Driven Spend Intelligence

KPMG applies machine learning techniques to classify and normalize unstructured spend data, identify anomalies and maverick spend patterns, and forecast category-level savings opportunities based on historical benchmarking and market trends. The approach combines proprietary analytical models developed across thousands of clients with industry-leading benchmarking datasets.

Real-Time Spend Visibility

The engagement designs dashboards with monthly or more frequent refresh cadences, giving procurement teams near-current visibility into maverick spend, supplier concentration risk, and category performance. Integration with client P2P and ERP systems enables rapid data flow from invoice through analytics layer.

Advanced Analytics & Benchmarking

KPMG's service includes detailed benchmarking against industry peers and market comparables for spend categories, pricing trends, and supplier performance metrics. The firm combines public market data, proprietary client benchmarks, and third-party market research to contextualize client spending and identify outliers.

Deployment Speed

While full engagements span 6-12 months, KPMG can deliver rapid-cycle diagnostics and quick-hit savings analysis in 8-12 weeks when scope is focused on top 10-20 spend categories, allowing early value realization and stronger business case for broader transformation.

Supplier & Category Insights

The service includes deep category-level analysis identifying supplier concentration risk, cost drivers, market dynamics, and consolidation opportunities. KPMG's category management teams provide subject-matter expertise in high-value categories such as indirect procurement, maintenance & repair, and transportation.

Data Enrichment Capabilities

The engagement includes data enrichment services such as supplier master cleansing, commodity code mapping, cost-center attribution, and enrichment with third-party supplier financial and risk data. KPMG works with data partners to append supplier credit, ESG, and geopolitical risk signals to enhance analytics.

Cross-System Data Integration

KPMG designs data integration architectures spanning ERP, P2P, invoice, payment, and supplier systems. The approach typically leverages APIs, ETL tools, or custom data pipelines depending on client technology stack. Integration includes reconciliation between systems and handling of edge cases (intercompany spend, accruals, currency).

AI-Driven Spend Intelligence

Corcentric leverages machine learning for automated spend classification, anomaly detection, and pattern recognition to identify savings opportunities faster, complemented by human procurement experts who validate findings and contextualize recommendations within client business strategy.

Real-Time Spend Visibility

While Corcentric's core strength is comprehensive historical spend analysis and benchmarking, its platform provides quarterly or semi-annual spend snapshots and updated visibility once implementation concludes, rather than continuous real-time monitoring; ongoing advisory retainers can maintain fresher insights.

Advanced Analytics & Benchmarking

Corcentric combines proprietary benchmark databases spanning millions of transactions across industries and geographies with advanced statistical analytics to identify savings potential, supplier consolidation opportunities, and category-level pricing comparisons tailored to client spending patterns.

Deployment Speed

Corcentric typically delivers initial findings and recommendations within 3–4 months through focused engagements, faster than building internal analytics capability from scratch, though full ROI realization and organizational adoption often extend 6–12 months.

Supplier & Category Insights

Corcentric performs deep supplier rationalization analysis, identifying consolidation opportunities and spend concentration risks, and delivers segment-level spend trends, pricing benchmarks, and category strategy recommendations backed by industry research and market intelligence.

Data Enrichment Capabilities

Corcentric enriches client spend data with third-party supplier intelligence, market pricing benchmarks, and industry classification standards to normalize and compare spending across internal categories, enabling cross-company spend comparisons and risk assessments.

Cross-System Data Integration

Corcentric integrates spend data from multiple ERP, P2P, and accounting systems, reconciling and deduplicating transactions across entities and currencies to create a unified spend foundation for analysis and benchmarking.

Revenue Band

$35B–$40B

Case Studies

3 engagements

Estimated Procurement Clients

500+

Years in Procurement Services

25+

Active Engagements

Ongoing engagements across Fortune 500 companies and mid-market organizations globally

Case Studies

3 engagements

Estimated Procurement Clients

500+

Years in Procurement Services

25+

Active Engagements

Ongoing with large Fortune 500 and mid-market clients across North America and Europe